Abstract
The physical size of typical digital images, in terms of the number of bytes of data one image contains, is large; e.g., a 1024 X 1024 image with 8 bits of data per pixel contains a megabyte of data. To transmit many such images over a network, sometimes over low-capacity phone lines to remote sites, or to store large numbers of images over a long period of time as part of the medical records for patients, the need for image compression arises to alleviate these large demands for image data storage and transmission capacity. This paper discusses image compression in terms of the information theory upon which it is based. The two basic categories of algorithms for implementing image compression are presented along with considerations for image quality and accuracy, which are of primary importance to the medical imaging community.
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